Publications associées à Inverse Analysis of Radiative Flux Maps for the Characterization of High Flux Sources

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Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Michaël Unser, Julien René Pierre Fageot, Harshit Gupta

We present a theoretical analysis and comparison of the effect of

ℓ _{ 1 }

versus

ℓ _{ 2 }

regularization for the resolution of ill-posed linear inverse and/or compressed sensing problems. Our formulation covers the most general setting where the s ...

IEEE2016

Inverse Analysis of Radiative Flux Maps for the Characterization of High Flux Sources

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Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

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Stability and Hypothesis Transfer Learning

Assessment of the Probability of Collapse of Structures Under Earthquakes

The regularized tau estimator: A robust and efficient solution to ill-posed linear inverse problems

Robust and adaptive approaches for Relative Geologic Time Estimation

Stability and Hypothesis Transfer Learning

Deriving fragility functions from bilinearized capacity curves for earthquake scenario modelling using the conditional spectrum

Sparse regularization for fiber ODF reconstruction: from the suboptimality of $\ell_2$ and $\ell_1$ priors to $\ell_0$

PURIFY: a new approach to radio-interferometric imaging

Sparsity-Based Data Reconstruction Models for Biomedical Imaging

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Sparse regularization methods in ultrafast ultrasound imaging